Related papers: Status of MadLoop/aMC@NLO
Next-to-leading order event generation for the Standard Model effective field theory has started to become available in the MadGraph5_aMC@NLO framework. In this talk we discuss some of the recent progresses in this direction, with a focus…
We apply the MC@NLO approach to the process of heavy flavour hadroproduction. MC@NLO is a method for matching next-to-leading order (NLO) QCD calculations and parton shower Monte Carlo (MC) simulations, with the following features: fully…
I review the status of today's theoretical description of Standard Model processes relevant for Tevatron and LHC analyses, and of the tools that are used in phenomenological studies. I will also discuss a few recent ideas to further refine…
In this presentation we review the current status in the automated evaluation of scattering amplitudes, with particular attention to the developments related with NLO calculations, which led to the construction of powerful multi-purpose…
Event generators simulate particle interactions using Monte Carlo techniques, providing the primary connection between experiment and theory in experimental high energy physics. These software packages, which are the first step in the…
Recently, Machine Learning (ML) has become a widely accepted method for significant progress that is rapidly evolving. Since it employs computational methods to teach machines and produce acceptable answers. The significance of the Machine…
We present for the first time the full automation of collider predictions matched with parton showers at the next-to-leading accuracy in QCD within non-trivial extensions of the Standard Model. The sole inputs required from the user are the…
The impact of NLO corrections, and in particular, the role of jet algorithms, is examined for a variety of processes at the Tevatron and LHC.
We present a next-to-leading order (NLO) treatment of the production of a new charged heavy vector boson, generically called W', at hadron colliders via the Drell-Yan process. We fully consider the interference effects with the Standard…
New techniques developed in connection with the NNLO corrections to the Higgs production rate at hadron colliders and some recent applications are reviewed.
Machine learning and AI have been recently embraced by many companies. Machine Learning Operations, (MLOps), refers to the use of continuous software engineering processes, such as DevOps, in the deployment of machine learning models to…
Machine Learning (ML) has become a fast-growing, trending approach in solution development in practice. Deep Learning (DL) which is a subset of ML, learns using deep neural networks to simulate the human brain. It trains machines to learn…
In these proceedings we report our progress in the development of the publicly available C++ library NJet for accurate calculations of high-multiplicity one-loop amplitudes. As a phenomenological application we present the first complete…
We present an extension of the expert mode of the MadAnalysis 5 program dedicated to the design or reinterpretation of high-energy physics collider analyses. We detail the predefined classes, functions and methods available to the user and…
Precision phenomenological studies of high-multiplicity scattering processes at collider experiments present a substantial theoretical challenge and are vitally important ingredients in experimental measurements. Machine learning technology…
This is the user's manual of MC@NLO 4.0. This package is a practical implementation, based upon the Fortran HERWIG and Herwig++ event generators, of the MC@NLO formalism, which allows one to incorporate NLO QCD matrix elements consistently…
NLO scattering amplitudes are provided by fully automated numerical tools, such as OpenLoops, for a very wide range of processes. In order to match the numerical precision of current and future collider experiments, the higher precision of…
We present a method for very fast repeated computations of higher-order cross sections in hadron-induced processes for arbitrary parton density functions. A full implementation of the method for computations of jet cross sections in…
The sustainable production of many bulk chemicals relies on heterogeneous catalysis. The rational design or improvement of the required catalysts critically depends on insights into the underlying mechanisms at the atomic scale. In recent…
Machine Learning Operations (MLOps) is becoming a highly crucial part of businesses looking to capitalize on the benefits of AI and ML models. This research presents a detailed review of MLOps, its benefits, difficulties, evolutions, and…